COMP/MATH 553: Algorithmic Game Theory

Fall 2016

Course Information

Course Description: Broad survey of topics at the interface of theoretical computer science and economics, with an emphasis on algorithms and computational complexity. Our main focus will be on algorithmic tools in mechanism design, algorithms and complexity theory for learning and computing Nash and market equilibria, and the price of anarchy. Case studies in Web search auctions, wireless spectrum auctions, matching markets, and network routing, and social networks.

Prerequisites: A course in algorithms (COMP 360 or equivalent) and probability (MATH 323 or equivalent).
No prior knowledge of Economics or Game Theory is required.

Assessment: The grade comprises the following components:

5% from games played in class; will play a few games with your classmates in class, and your score depends on your performance in these games.

5% from class participation.

45% from homework problems; there will be 3 problem sets.

45% from the final exam.

Course Outline

There is a significant dynamic component to the course, as topics drop
in and out, or get longer or shorter treatment, depending on audience
interest/reaction/resistance. We consider this a feature. Given this,
here is a rough outline of the course material.

Lectures

The list below will contain notes/presentations produced by the instructor.

Lecture 1 (Sept 6th): Introduction to Algorithmic Game Theory: Incentives in Large Systems; Games; Nash Equilibria and their computation; the Price of Anarchy; Mechanism Design. Slides | Slides in pdf without animation